About
Data analytics student with hands-on experience developing end-to-end projects, executing SQL queries across 75,000+ records, and designing Power BI dashboards that identified ₹19.93M in combined revenue leakage and wasted ad spend. Pursuing a data analyst internship to apply analytical expertise to real business challenges.
Skills & Expertise (19)
Work Experience
Business Performance Analyst
Blinkit
Apr 2026 - May 2026
Analyzed 9 marketing campaigns across 5,400+ daily performance records and 75,000+ inventory transactions spanning 11 product categories, uncovering ₹19.93M in combined revenue leakage and wasted ad spend across a 4-page Power BI dashboard. Surfaced ₹8.18M in wasted campaign spend using DAX and SQL window functions, isolating low-converting campaigns by audience segment. Uncovered ₹11.75M in inventory revenue leakage at 33.67% revenue realization, with Pet Care as the worst category at 54.1% damage-driven loss. Engineered complex SQL queries utilizing CTEs, multi-table joins, and RANK() OVER PARTITION BY to enable filter-aware dynamic subtitles across all dashboard pages.
Analytics Dashboard Developer
YouTube Channel
Mar 2026 - Apr 2026
Queried and classified 223 videos across 2 years of channel data using a keyword-based SQL CASE-WHEN system, mapping performance across 11 categories to identify monetization drivers. Identified Career/Jobs as the highest revenue-efficiency category, matching top content on CPM (₹11.44 avg) and RPM despite 40% lower view volume. Engineered custom Growth Rate and Impact Score KPIs using weighted SQL formulas, surfacing August 2020 as peak performance month with a 10.02 avg growth rate. Built a 3-page executive dashboard covering subscriber conversion, global geography across 6 continents, and monetization analysis with a continent slicer updating all KPIs dynamically.
Data Analyst
Rainfall-Based Flood Risk Visualization
Jan 2026 - Feb 2026
Analyzed 25 years of coastal Tamil Nadu rainfall data using Python and Pandas; developed and calibrated a threshold-based anomaly detection system set at 125% of the historical average. Identified three high-risk years within a 25-year span by statistically flagging periods of elevated flood risk, replacing arbitrary cutoff methods with data-driven justification. Developed multi-layer Matplotlib visualization integrating dynamic threshold lines, year-wise trends, and highlighted anomaly scatter points, translating raw climate data into actionable risk context.
Education
Bachelor of Technology (BTech), Computer Science & Engineering - MLR Institute of Technology
2025 - 2029 · India
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Skills (19)
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